From 8bb459c7ba4e5b91eb3a684a7a57e798e2a862f6 Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Mon, 27 May 2024 17:24:07 +0000
Subject: [PATCH 1/6] [pre-commit.ci] pre-commit autoupdate
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

updates:
- [github.com/astral-sh/ruff-pre-commit: v0.4.1 → v0.4.5](https://github.com/astral-sh/ruff-pre-commit/compare/v0.4.1...v0.4.5)
---
 .pre-commit-config.yaml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index 964e292ab85..9811dbd3910 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -27,7 +27,7 @@ repos:
         - --exclude=binder/
         - --exclude=versioneer.py
 - repo: https://github.com/astral-sh/ruff-pre-commit
-  rev: v0.4.1
+  rev: v0.4.5
   hooks:
     - id: ruff
       args: ["--fix", "--output-format=full"]

From 6bd28039a459eaf8069ea8b0a5b34c4b10005765 Mon Sep 17 00:00:00 2001
From: Virgile Andreani <virgile@pymc-devs.org>
Date: Tue, 28 May 2024 05:32:58 -0400
Subject: [PATCH 2/6] Add _version.py to exclude list of linter

---
 pyproject.toml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/pyproject.toml b/pyproject.toml
index 83afadc67bb..8458b8f13f3 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -7,7 +7,7 @@ addopts = ["--color=yes"]
 [tool.ruff]
 line-length = 100
 target-version = "py310"
-exclude = ["versioneer.py"]
+extend-exclude = ["versioneer.py", "_version.py"]
 
 [tool.ruff.lint]
 select = ["D", "E", "F", "I", "UP", "W", "RUF"]

From a7b3e07ef4b155a3d75de55c9966b99f9bab3602 Mon Sep 17 00:00:00 2001
From: Virgile Andreani <virgile@pymc-devs.org>
Date: Tue, 28 May 2024 05:33:29 -0400
Subject: [PATCH 3/6] Remove deprecated ruff config option

---
 pyproject.toml | 1 -
 1 file changed, 1 deletion(-)

diff --git a/pyproject.toml b/pyproject.toml
index 8458b8f13f3..160374d25fd 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -11,7 +11,6 @@ extend-exclude = ["versioneer.py", "_version.py"]
 
 [tool.ruff.lint]
 select = ["D", "E", "F", "I", "UP", "W", "RUF"]
-ignore-init-module-imports = true
 ignore = [
   "E501",
   "F841", # Local variable name is assigned to but never used

From a5844f8cdb562945427079ca9565256b9a9fd54e Mon Sep 17 00:00:00 2001
From: Virgile Andreani <virgile@pymc-devs.org>
Date: Tue, 28 May 2024 05:34:51 -0400
Subject: [PATCH 4/6] Apply safe ruff fix

---
 pymc/model/core.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/pymc/model/core.py b/pymc/model/core.py
index 0cf8bd26cf6..874d52f9bd6 100644
--- a/pymc/model/core.py
+++ b/pymc/model/core.py
@@ -209,7 +209,7 @@ def __init_subclass__(cls, **kwargs):
     def __call__(cls, *args, **kwargs):
         # We type hint Model here so type checkers understand that Model is a context manager.
         # This metaclass is only used for Model, so this is safe to do. See #6809 for more info.
-        instance: "Model" = cls.__new__(cls, *args, **kwargs)
+        instance: Model = cls.__new__(cls, *args, **kwargs)
         with instance:  # appends context
             instance.__init__(*args, **kwargs)
         return instance

From aea690adc8458b480562a5ed56fc3c66a99d2c52 Mon Sep 17 00:00:00 2001
From: Virgile Andreani <virgile@pymc-devs.org>
Date: Tue, 28 May 2024 05:37:07 -0400
Subject: [PATCH 5/6] Apply unsafe f-string related ruff fixes

---
 pymc/backends/base.py                |  8 ++++----
 pymc/distributions/multivariate.py   |  8 ++++----
 pymc/sampling/forward.py             |  5 ++---
 pymc/sampling/mcmc.py                |  5 +----
 pymc/sampling/parallel.py            |  8 ++++----
 pymc/step_methods/hmc/integration.py |  2 +-
 pymc/step_methods/metropolis.py      |  2 +-
 pymc/variational/inference.py        |  4 ++--
 pymc/variational/opvi.py             | 12 ++++++------
 tests/variational/test_opvi.py       |  2 +-
 10 files changed, 26 insertions(+), 30 deletions(-)

diff --git a/pymc/backends/base.py b/pymc/backends/base.py
index 7854cc09313..477723a6970 100644
--- a/pymc/backends/base.py
+++ b/pymc/backends/base.py
@@ -186,7 +186,7 @@ def _set_sampler_vars(self, sampler_vars):
         for stats in sampler_vars:
             for key, dtype in stats.items():
                 if dtypes.setdefault(key, dtype) != dtype:
-                    raise ValueError("Sampler statistic %s appears with " "different types." % key)
+                    raise ValueError(f"Sampler statistic {key} appears with different types.")
 
         self.sampler_vars = sampler_vars
 
@@ -247,7 +247,7 @@ def get_sampler_stats(
 
         sampler_idxs = [i for i, s in enumerate(self.sampler_vars) if stat_name in s]
         if not sampler_idxs:
-            raise KeyError("Unknown sampler stat %s" % stat_name)
+            raise KeyError(f"Unknown sampler stat {stat_name}")
 
         vals = np.stack(
             [self._get_sampler_stats(stat_name, i, burn, thin) for i in sampler_idxs], axis=-1
@@ -388,7 +388,7 @@ def __getitem__(self, idx):
             return self.get_values(var, burn=burn, thin=thin)
         if var in self.stat_names:
             return self.get_sampler_stats(var, burn=burn, thin=thin)
-        raise KeyError("Unknown variable %s" % var)
+        raise KeyError(f"Unknown variable {var}")
 
     _attrs = {"_straces", "varnames", "chains", "stat_names", "_report"}
 
@@ -512,7 +512,7 @@ def get_sampler_stats(
             List or ndarray depending on parameters.
         """
         if stat_name not in self.stat_names:
-            raise KeyError("Unknown sampler statistic %s" % stat_name)
+            raise KeyError(f"Unknown sampler statistic {stat_name}")
 
         if chains is None:
             chains = self.chains
diff --git a/pymc/distributions/multivariate.py b/pymc/distributions/multivariate.py
index 347a6e2539a..359b0743dd8 100644
--- a/pymc/distributions/multivariate.py
+++ b/pymc/distributions/multivariate.py
@@ -1047,11 +1047,11 @@ def WishartBartlett(name, S, nu, is_cholesky=False, return_cholesky=False, initv
         tril_testval = None
 
     c = pt.sqrt(
-        ChiSquared("%s_c" % name, nu - np.arange(2, 2 + n_diag), shape=n_diag, initval=diag_testval)
+        ChiSquared(f"{name}_c", nu - np.arange(2, 2 + n_diag), shape=n_diag, initval=diag_testval)
     )
-    pm._log.info("Added new variable %s_c to model diagonal of Wishart." % name)
-    z = Normal("%s_z" % name, 0.0, 1.0, shape=n_tril, initval=tril_testval)
-    pm._log.info("Added new variable %s_z to model off-diagonals of Wishart." % name)
+    pm._log.info(f"Added new variable {name}_c to model diagonal of Wishart.")
+    z = Normal(f"{name}_z", 0.0, 1.0, shape=n_tril, initval=tril_testval)
+    pm._log.info(f"Added new variable {name}_z to model off-diagonals of Wishart.")
     # Construct A matrix
     A = pt.zeros(S.shape, dtype=np.float32)
     A = pt.set_subtensor(A[diag_idx], c)
diff --git a/pymc/sampling/forward.py b/pymc/sampling/forward.py
index 23b3a601658..ce51f5cc720 100644
--- a/pymc/sampling/forward.py
+++ b/pymc/sampling/forward.py
@@ -419,7 +419,7 @@ def sample_prior_predictive(
 
     data = {k: np.stack(v) for k, v in zip(names, values)}
     if data is None:
-        raise AssertionError("No variables sampled: attempting to sample %s" % names)
+        raise AssertionError(f"No variables sampled: attempting to sample {names}")
 
     prior: dict[str, np.ndarray] = {}
     for var_name in vars_:
@@ -765,8 +765,7 @@ def sample_posterior_predictive(
         samples = len(_trace)
     else:
         raise TypeError(
-            "Do not know how to compute number of samples for trace argument of type %s"
-            % type(_trace)
+            f"Do not know how to compute number of samples for trace argument of type {type(_trace)}"
         )
 
     assert samples is not None
diff --git a/pymc/sampling/mcmc.py b/pymc/sampling/mcmc.py
index f2ef43e8b58..c09cb163f5a 100644
--- a/pymc/sampling/mcmc.py
+++ b/pymc/sampling/mcmc.py
@@ -697,10 +697,7 @@ def joined_blas_limiter():
         msg = "Tuning was enabled throughout the whole trace."
         _log.warning(msg)
     elif draws < 100:
-        msg = (
-            "Only %s samples per chain. Reliable r-hat and ESS diagnostics require longer chains for accurate estimate."
-            % draws
-        )
+        msg = f"Only {draws} samples per chain. Reliable r-hat and ESS diagnostics require longer chains for accurate estimate."
         _log.warning(msg)
 
     auto_nuts_init = True
diff --git a/pymc/sampling/parallel.py b/pymc/sampling/parallel.py
index 9f950f621f1..a34947c7064 100644
--- a/pymc/sampling/parallel.py
+++ b/pymc/sampling/parallel.py
@@ -58,7 +58,7 @@ def __init__(self, exc, tb):
         tb = traceback.format_exception(type(exc), exc, tb)
         tb = "".join(tb)
         self.exc = exc
-        self.tb = '\n"""\n%s"""' % tb
+        self.tb = f'\n"""\n{tb}"""'
 
     def __reduce__(self):
         return rebuild_exc, (self.exc, self.tb)
@@ -216,7 +216,7 @@ def __init__(
         mp_ctx,
     ):
         self.chain = chain
-        process_name = "worker_chain_%s" % chain
+        process_name = f"worker_chain_{chain}"
         self._msg_pipe, remote_conn = multiprocessing.Pipe()
 
         self._shared_point = {}
@@ -228,7 +228,7 @@ def __init__(
                 size *= int(dim)
             size *= dtype.itemsize
             if size != ctypes.c_size_t(size).value:
-                raise ValueError("Variable %s is too large" % name)
+                raise ValueError(f"Variable {name} is too large")
 
             array = mp_ctx.RawArray("c", size)
             self._shared_point[name] = (array, shape, dtype)
@@ -388,7 +388,7 @@ def __init__(
         mp_ctx=None,
     ):
         if any(len(arg) != chains for arg in [seeds, start_points]):
-            raise ValueError("Number of seeds and start_points must be %s." % chains)
+            raise ValueError(f"Number of seeds and start_points must be {chains}.")
 
         if mp_ctx is None or isinstance(mp_ctx, str):
             # Closes issue https://github.com/pymc-devs/pymc/issues/3849
diff --git a/pymc/step_methods/hmc/integration.py b/pymc/step_methods/hmc/integration.py
index c8defa2e819..2d1e725cde9 100644
--- a/pymc/step_methods/hmc/integration.py
+++ b/pymc/step_methods/hmc/integration.py
@@ -51,7 +51,7 @@ def __init__(self, potential: QuadPotential, logp_dlogp_func):
     def compute_state(self, q: RaveledVars, p: RaveledVars):
         """Compute Hamiltonian functions using a position and momentum."""
         if q.data.dtype != self._dtype or p.data.dtype != self._dtype:
-            raise ValueError("Invalid dtype. Must be %s" % self._dtype)
+            raise ValueError(f"Invalid dtype. Must be {self._dtype}")
 
         logp, dlogp = self._logp_dlogp_func(q)
 
diff --git a/pymc/step_methods/metropolis.py b/pymc/step_methods/metropolis.py
index 6c3f2b8a095..a816728cefb 100644
--- a/pymc/step_methods/metropolis.py
+++ b/pymc/step_methods/metropolis.py
@@ -178,7 +178,7 @@ def __init__(
         elif S.ndim == 2:
             self.proposal_dist = MultivariateNormalProposal(S)
         else:
-            raise ValueError("Invalid rank for variance: %s" % S.ndim)
+            raise ValueError(f"Invalid rank for variance: {S.ndim}")
 
         self.scaling = np.atleast_1d(scaling).astype("d")
         self.tune = tune
diff --git a/pymc/variational/inference.py b/pymc/variational/inference.py
index 42dad4a404b..0c596d2d981 100644
--- a/pymc/variational/inference.py
+++ b/pymc/variational/inference.py
@@ -72,8 +72,8 @@ def _maybe_score(self, score):
             score = returns_loss
         elif score and not returns_loss:
             warnings.warn(
-                "method `fit` got `score == True` but %s "
-                "does not return loss. Ignoring `score` argument" % self.objective.op
+                f"method `fit` got `score == True` but {self.objective.op} "
+                "does not return loss. Ignoring `score` argument"
             )
             score = False
         else:
diff --git a/pymc/variational/opvi.py b/pymc/variational/opvi.py
index 35f924c1a7b..e1165a874cd 100644
--- a/pymc/variational/opvi.py
+++ b/pymc/variational/opvi.py
@@ -375,7 +375,7 @@ def step_function(
         if fn_kwargs is None:
             fn_kwargs = {}
         if score and not self.op.returns_loss:
-            raise NotImplementedError("%s does not have loss" % self.op)
+            raise NotImplementedError(f"{self.op} does not have loss")
         updates = self.updates(
             obj_n_mc=obj_n_mc,
             tf_n_mc=tf_n_mc,
@@ -416,7 +416,7 @@ def score_function(
         if fn_kwargs is None:
             fn_kwargs = {}
         if not self.op.returns_loss:
-            raise NotImplementedError("%s does not have loss" % self.op)
+            raise NotImplementedError(f"{self.op} does not have loss")
         if more_replacements is None:
             more_replacements = {}
         loss = self(sc_n_mc, more_replacements=more_replacements)
@@ -496,13 +496,13 @@ def apply(self, f):  # pragma: no cover
     def __call__(self, f=None):
         if self.has_test_function:
             if f is None:
-                raise ParametrizationError("Operator %s requires TestFunction" % self)
+                raise ParametrizationError(f"Operator {self} requires TestFunction")
             else:
                 if not isinstance(f, TestFunction):
                     f = TestFunction.from_function(f)
         else:
             if f is not None:
-                warnings.warn("TestFunction for %s is redundant and removed" % self, stacklevel=3)
+                warnings.warn(f"TestFunction for {self} is redundant and removed", stacklevel=3)
             else:
                 pass
             f = TestFunction()
@@ -555,7 +555,7 @@ def setup(self, approx):
     @classmethod
     def from_function(cls, f):
         if not callable(f):
-            raise ParametrizationError("Need callable, got %r" % f)
+            raise ParametrizationError(f"Need callable, got {f!r}")
         obj = TestFunction()
         obj.__call__ = f
         return obj
@@ -1512,7 +1512,7 @@ def vars_names(vs):
                 found.name = name + "_vi_random_slice"
                 break
         else:
-            raise KeyError("%r not found" % name)
+            raise KeyError(f"{name!r} not found")
         return found
 
     @node_property
diff --git a/tests/variational/test_opvi.py b/tests/variational/test_opvi.py
index a196a2b60c2..5b02571898a 100644
--- a/tests/variational/test_opvi.py
+++ b/tests/variational/test_opvi.py
@@ -261,7 +261,7 @@ def test_logq_mini_2_sample_2_var(parametric_grouped_approxes, three_var_model):
 
 def test_logq_globals(three_var_approx):
     if not three_var_approx.has_logq:
-        pytest.skip("%s does not implement logq" % three_var_approx)
+        pytest.skip(f"{three_var_approx} does not implement logq")
     approx = three_var_approx
     logq, symbolic_logq = approx.set_size_and_deterministic(
         [approx.logq, approx.symbolic_logq], 1, 0

From d96ccf8cb9ab09f03f0484bed624f6c84a359f41 Mon Sep 17 00:00:00 2001
From: Virgile Andreani <virgile@pymc-devs.org>
Date: Tue, 28 May 2024 05:47:16 -0400
Subject: [PATCH 6/6] Remove a few more uses of .format

---
 pymc/distributions/shape_utils.py | 14 ++++----------
 pymc/gp/util.py                   |  5 ++---
 pymc/printing.py                  | 12 ++++++------
 3 files changed, 12 insertions(+), 19 deletions(-)

diff --git a/pymc/distributions/shape_utils.py b/pymc/distributions/shape_utils.py
index 7a4b0a95c18..1d0fee588d0 100644
--- a/pymc/distributions/shape_utils.py
+++ b/pymc/distributions/shape_utils.py
@@ -141,11 +141,8 @@ def broadcast_dist_samples_shape(shapes, size=None):
     if size is None:
         broadcasted_shape = np.broadcast_shapes(*shapes)
         if broadcasted_shape is None:
-            raise ValueError(
-                "Cannot broadcast provided shapes {} given size: {}".format(
-                    ", ".join([f"{s}" for s in shapes]), size
-                )
-            )
+            tmp = ", ".join([f"{s}" for s in shapes])
+            raise ValueError(f"Cannot broadcast provided shapes {tmp} given size: {size}")
         return broadcasted_shape
     shapes = [_check_shape_type(s) for s in shapes]
     _size = to_tuple(size)
@@ -154,11 +151,8 @@ def broadcast_dist_samples_shape(shapes, size=None):
     try:
         broadcast_shape = np.broadcast_shapes(*sp_shapes)
     except ValueError:
-        raise ValueError(
-            "Cannot broadcast provided shapes {} given size: {}".format(
-                ", ".join([f"{s}" for s in shapes]), size
-            )
-        )
+        tmp = ", ".join([f"{s}" for s in shapes])
+        raise ValueError(f"Cannot broadcast provided shapes {tmp} given size: {size}")
     broadcastable_shapes = []
     for shape, sp_shape in zip(shapes, sp_shapes):
         if _size == shape[: len(_size)]:
diff --git a/pymc/gp/util.py b/pymc/gp/util.py
index ba20130a3d6..4a4a18fda42 100644
--- a/pymc/gp/util.py
+++ b/pymc/gp/util.py
@@ -143,9 +143,8 @@ def getter(self):
                 value = getattr(self, name, None)
                 if value is None:
                     raise AttributeError(
-                        "'{}' not set.  Provide as argument "
-                        "to condition, or call 'prior' "
-                        "first".format(name.lstrip("_"))
+                        f"'{name.lstrip('_')}' not set.  Provide as argument "
+                        "to condition, or call 'prior' first"
                     )
                 else:
                     return value
diff --git a/pymc/printing.py b/pymc/printing.py
index 6c6bdbb71d2..f1a34c6f95a 100644
--- a/pymc/printing.py
+++ b/pymc/printing.py
@@ -65,12 +65,11 @@ def str_for_dist(
             else r"\\operatorname{Unknown}"
         )
         if include_params:
+            params = ",~".join([d.strip("$") for d in dist_args])
             if print_name:
-                return r"${} \sim {}({})$".format(
-                    print_name, op_name, ",~".join([d.strip("$") for d in dist_args])
-                )
+                return rf"${print_name} \sim {op_name}({params})$"
             else:
-                return r"${}({})$".format(op_name, ",~".join([d.strip("$") for d in dist_args]))
+                return rf"${op_name}({params})$"
 
         else:
             if print_name:
@@ -83,10 +82,11 @@ def str_for_dist(
             dist.owner.op._print_name[0] if hasattr(dist.owner.op, "_print_name") else "Unknown"
         )
         if include_params:
+            params = ", ".join(dist_args)
             if print_name:
-                return r"{} ~ {}({})".format(print_name, dist_name, ", ".join(dist_args))
+                return rf"{print_name} ~ {dist_name}({params})"
             else:
-                return r"{}({})".format(dist_name, ", ".join(dist_args))
+                return rf"{dist_name}({params})"
         else:
             if print_name:
                 return rf"{print_name} ~ {dist_name}"